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Quantitative CT Characteristics of Cluster Phenotypes in the Severe Asthma Research Program Cohorts

Authors :
Abhaya P, Trivedi
Chase, Hall
Charles W, Goss
Daphne, Lew
James G, Krings
Mary Clare, McGregor
Maanasi, Samant
Jered P, Sieren
Huashi, Li
Ken B, Schechtman
Joshua, Schirm
Stephen, McEleney
Sam, Peterson
Wendy C, Moore
Eugene R, Bleecker
Deborah A, Meyers
Elliot, Israel
George R, Washko
Bruce D, Levy
Joseph K, Leader
Sally E, Wenzel
John V, Fahy
Mark L, Schiebler
Sean B, Fain
Nizar N, Jarjour
David T, Mauger
Joseph M, Reinhardt
John D, Newell
Eric A, Hoffman
Mario, Castro
Ajay, Sheshadri
Brenda, Phillips
Source :
Radiology. 304:450-459
Publication Year :
2022
Publisher :
Radiological Society of North America (RSNA), 2022.

Abstract

Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4

Details

ISSN :
15271315 and 00338419
Volume :
304
Database :
OpenAIRE
Journal :
Radiology
Accession number :
edsair.doi.dedup.....85ee8311fc78e41e5dcd7bf9027ce8ec
Full Text :
https://doi.org/10.1148/radiol.210363